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Record W1526857352 · doi:10.1086/510061

Deep Submillimeter Observations of Two Lyα‐emitting Galaxies at<i>z</i>∼ 6.5

2007· article· en· W1526857352 on OpenAlexaff
Tracy Webb, Kim‐Vy Tran, S. J. Lilly, P. van der Werf

Bibliographic record

VenueThe Astrophysical Journal · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsMcGill University
Fundersnot available
KeywordsPhysicsGalaxyAstrophysicsConfusionStar formationAstronomyPopulationHubble Deep FieldSubmillimeter waveRedshiftMillimeter

Abstract

fetched live from OpenAlex

We present deep submillimeter imaging of two spectroscopically confirmed z ~ 6.5 Lyα emitters (LAEs) in the Subaru Deep Field. Although we reach the nominal confusion limit at 850 μm, neither LAE is detected at 850 or 450 μm; thus, we conclude that the LAEs do not contain large dust masses (<2.3 × 10 8 and <5.7 × 10 8 M ☉ ). The limit on their average L FIR / L UV ratios (≲35) is substantially lower than seen for most submillimeter-selected galaxies at z ~ 3 and is within the range of values exhibited by Lyman break galaxies. We place upper limits on their individual star formation rates of ≲248 and ≲613 M ☉ yr -1 , and on the cosmic star formation rate density of the z ~ 6.5 LAE population of ≲5.0 × 10 -2 M ☉ yr -1 Mpc -3 . In the two submillimeter pointings, we also serendipitously detect seven sources at 850 μm that we estimate to lie at 1 < z < 5.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.232
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2007
Admission routes1
Has abstractyes

Explore more

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